GenomicPlot
Bioc currentPlot profiles of next generation sequencing data in genomic features
Release Lineage
Entered 3.18 · Oct 25, 2023
Current · Requires R 4.6
Description
Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
62 57 exported
Complexity
12.2 avg / 101 max
Call network
62 nodes / 113 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
14,276
Files
121
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
57
Internal functions
5
Testing
Has tests
Yes
Test-to-code ratio
0.07
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
50%
Unsafe pattern score
0
Dep constraint coverage
32.4%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.4.0
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
6
First release
2024-04-08
Latest release
2026-04-28
Avg cadence
141 days
Cold removal rate
–
Dep drift
4
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 67 (5 internal)
- Examples that run
- 100%61 run in a plain check
- Exported functions with examples
- 98%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Repository practices
4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/shuye2009/genomicplot on 2026-10-18.
GitHub Pages site last deployed 2023-05-08
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| gencode.v19.annotation_chr19.gtf.granges | – | – | – |
| gf5_genomic | list | 7 elements | No other package |
| gf5_meta | list | 7 elements | No other package |
| test_file1 | data.frame | 25 × 4 | No other package |
| test_file2 | data.frame | 25 × 3 | No other package |
| test_file3 | data.frame | 17 × 2 | No other package |
| test_file4 | data.frame | 17 × 1 | No other package |
Topics
People
- Shuye Pu author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("GenomicPlot")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.